Excerpt

To glimpse the engaging writing style of Interpersonal Divide in the Age of the Machine, here’s the introduction of Chapter Three, “Big Data, Little People,” discussing a machine world in which media explain everything but “why”:

How People Became Nodes

In Isaac Asimov’s famous science fiction story, “Feminine Intuition,” published in his 1976 collection The Bicentennial Man, researchers created the first robot not pre-programmed to do specific tasks. They labeled the assembly of this model robot “intuition” so as not to leave the impression that the machine was “uncontrolled” or worse, uncontrollable.

Because people might fear irrepressible machines, Asimov begins this story with his fabled “Three Laws of Robotics”:

A robot may not injure a human being or, though inaction, allow a human being to come to harm.

A robot must obey the orders given it by human beings except where such orders would conflict with the First Law.

A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.[i]

The title, “Feminine Intuition,” affirms a belief that women were better than men at intuition. A female robot “could make correlations far more rapidly and far more precisely than a man could,” the protagonist researcher states. “In a day, it could make and discard as many correlations as a man could in ten years. Furthermore, it would work in a truly random fashion, whereas a man would have a strong bias based on preconception and on what is already believed.”[ii]

The company, United States Robots, builds the machine; but there is a problem. “The trouble is the matter of recognition,” the protagonist states. The robot is “correlating magnificently. She can correlate on any subject, but once she’s done so, she can’t recognize a valuable result from a valueless one. It’s not an easy problem, judging how to program a robot to tell a significant correlation when you don’t know what correlations she will be making.”[iii]

Reading this story some 40 years later, one can recognize the gender stereotypes but also Asimov’s prophetic vision. Big data reduce the global millions of Internet users into nodes—interactive re-distribution points—or little people, using personal, professional, educational, governmental, psychological, sociological and, most importantly, consumer demographics and psychographics to make seemingly instantaneous correlations of what each user-node likes, dislikes and is most likely to buy. From an economic standpoint, it really does not matter why the person is buying a product or service; that would be “causation” or, in simpler terms, the reason for the sale. No. All that matters is the sale.